Internetwork dynamic connectivity effectively differentiates schizophrenic patients from healthy controls

Neuroreport. 2014 Dec 3;25(17):1344-9. doi: 10.1097/WNR.0000000000000267.


Increasingly more neuroimaging studies have shown that the complex symptoms of schizophrenia are linked to disrupted neural circuits and dysconnectivity of intrinsic connectivity networks. Previous studies have assumed temporal stationarity of resting-state functional connectivity, whereas temporal dynamics have rarely been explored. Here, we utilized resting-state functional MRI with a sliding window approach to measure the amplitude of low-frequency fluctuations (ALFFs) in functional connectivity in 24 patients with schizophrenia and 25 healthy controls. We found that there were significant differences in the ALFFs of specific connections, the majority of which were located between the intrinsic connectivity networks. Importantly, the experimental results of a multivariate pattern analysis of these ALFF measures showed that 81.3% (P<0.0009) of the participants were correctly classified as either schizophrenic patients or healthy controls by leave-one-out cross-validation. Our results show significant abnormality in the dynamics of internetwork functional connectivity in schizophrenia, which contributes toward the characterization and differentiation of schizophrenic patients, and may be used as a potential biomarker.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Antipsychotic Agents / therapeutic use
  • Brain / physiopathology*
  • Diagnosis, Computer-Assisted
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods
  • Male
  • Multivariate Analysis
  • Neural Pathways / physiopathology
  • Rest
  • Schizophrenia / diagnosis
  • Schizophrenia / drug therapy
  • Schizophrenia / physiopathology*
  • Signal Processing, Computer-Assisted
  • Support Vector Machine


  • Antipsychotic Agents